Swapping DNA

Assembly Automation

ISSN: 0144-5154

Article publication date: 18 April 2008

Citation

Loughlin, C. (2008), "Swapping DNA", Assembly Automation, Vol. 28 No. 2. https://doi.org/10.1108/aa.2008.03328baa.001

Publisher

:

Emerald Group Publishing Limited

Copyright © 2008, Emerald Group Publishing Limited


Swapping DNA

Article Type: Editorial From: Assembly Automation, Volume 28, Issue 2.

The buzzword of the moment seems to be “Evolvability” and it is interesting to compare Evolvable Assembly Systems with the various theories and alternatives for evolution in the natural world. Without judging for a moment the conflicting theories of evidence-based Darwinian evolution or the DNA swapping theories of Dr J Craig Venter or the more faith- based creationist beliefs, let us examine how these three theories map out if applied to automated assembly systems.

I can remember a long time ago seeing one of those “staff motivation” posters that said words to the effect of “Quality is getting it right first time”. This certainly has it appeal, especially when compared with the alternative of “getting it wrong first time”. This mantra maps pretty directly into our creationist beliefs, only in this case it is us engineers who put ourselves in the position of gods. We hold lots of meetings and decide in advance that in our view the best way of doing something is Plan X. This is based on previous experience and a varying degree of wishful thinking. Having decided on Plan X, drawings are made and a machine is produced and then it is switched on. With luck it is not actually a “bad” design and should more or less work as originally intended. If it does not then it could be that one part of it needs to be modified. However, considering the machine was designed with a “getting it right first time” approach the whole idea of making a change is an anathema, and so fixing the problem is likely to be far from straightforward or even impossible.

By contrast Darwinian evolution involves tinkering with the minutia and seeing if the new design works better or is more “fit for purpose” than the previous version. To map this into our automated system it could, for example, equate to the fine adjustment of a bowl feeder separation track so that blockages become less frequent. Automated systems involve inputs and outputs evolution enables the system to acquire better inputs (e.g. less blockages) and provide better outputs (e.g. more components per hour).

Evolvable Assembly Systems are specifically designed to be able to modify their various parts so that each stage of an assembly process can be adjusted or evolve, either to improve itself or to respond to changes in inputs. This flexibility has clear advantages but does inevitably result in a more complex and possibly more expensive system. Complex systems take longer to design but the hope is that they will have a longer operational life because they are able to adapt to changing requirements. This also reduces the actual lifetime cost of implementation so it can be less than inflexible solutions.

DNA swapping theories suggest that evolution does not take place by tinkering with minutia but by swapping fundamental characteristics. Farmers have been doing this for years either by, for example, grafting a branch from one type of apple tree onto the root stock of another or cross- breeding animals to, for example, create a new breed of cow that produces milk with a lower fat content.

This DNA swapping works an awful lot faster than, for example, waiting for 50 generations of slightly lower fat producing cows to evolve into a semi-skimmed variety.

Returning to our Evolvable Assembly System this DNA swapping equates to swapping one module for another as opposed to tinkering with modules already in the system. As an example this could mean exchanging a suction gripper for one that uses magnetism if this is more suitable for the part concerned.

Our theme for this issue is “Modular Assembly” and it is clear from our many contributions that our ideas are constantly evolving.

Clive Loughlin